Major depression (MDD) is a highly prevalent disease associated with significant morbidity and mortality and estimated to be one of the leading causes of disability worldwide. A variety of antidepressant drugs, psychotherapies, and non-drug somatic therapies have demonstrated efficacy in acute treatment trials. However, the majority of patients in these trials do not attain remission, increasing the risk for the development of chronic depression, suicide, substance abuse and several serious medical disorders. A major unmet need in the field is the identification of predictors of response to individual treatment modalities, as has been utilized other branches of medicine such as oncology and infectious disease, to improve patient outcome. In view of advances in functional brain imaging, molecular neurobiology and genetics, and a number of promising findings in small studies, it is propitious to conduct both hypothesis-generating and hypothesis-testing studies to determine whether a concatenation of factors, taken together, predict antidepressant treatment response. To achieve that goal, we propose a 3-arm, 12-week treatment trial led by Philip T. Ninan, M.D. of 400 treament naive adult depressed patients randomized to one of the following treatments after a 1 week placebo treatment period: 1) escitalopram, an SSRI;2) duloxetine, an SNRI and 3) CBT. A series of behavioral and biological measures will be obtained that include functional brain imaging (fMRI) led by Helen S. Mayberg, M.D., several genetic polymorphisms led by Joseph F. Cubells, M.D., Ph.D. and Elisabeth Binder, M.D., Ph.D., indices of HPA axis activity, markers of immune and inflammatory function, as well as measures of personality, early life trauma, depression and anxiety, and cognitive function. In addition, in a study led by Michael J. Owens, Ph.D. both PET and an ex vivo method will be utilized to determine the relationship of the magnitude of SERT occupancy to clinical response in the escitalopram and duloxetine treatment groups and, moreover, the ex vivo method will be used to assess the importance of NET occupancy in treatment response to duloxetine. A Special Scientific Procedures, Statistical Modeling Core, led by Mary Kelley, Ph.D. will seek to determine which measure and/or combination of measures leads to predictors of response to the three treatments under study. Delineation of patient characteristics that predict treatment response to a specific treatment modality will dramatically improve patient outcomes and reduce the risk of inadequate treatment.